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García Laborda, Jesús, Arús Hita, Jorge, Mashhadi, Amir. (1403). Introduction: Language Teaching Feedback and Assessment Aided by Digital Technologies. سامانه نشریات, 15(2), 3-5. doi: 10.22055/rals.2024.19543
Jesús García Laborda; Jorge Arús Hita; Amir Mashhadi. "Introduction: Language Teaching Feedback and Assessment Aided by Digital Technologies". سامانه نشریات, 15, 2, 1403, 3-5. doi: 10.22055/rals.2024.19543
García Laborda, Jesús, Arús Hita, Jorge, Mashhadi, Amir. (1403). 'Introduction: Language Teaching Feedback and Assessment Aided by Digital Technologies', سامانه نشریات, 15(2), pp. 3-5. doi: 10.22055/rals.2024.19543
García Laborda, Jesús, Arús Hita, Jorge, Mashhadi, Amir. Introduction: Language Teaching Feedback and Assessment Aided by Digital Technologies. سامانه نشریات, 1403; 15(2): 3-5. doi: 10.22055/rals.2024.19543

Introduction: Language Teaching Feedback and Assessment Aided by Digital Technologies

Journal of Research in Applied Linguistics
مقاله 1، دوره 15، شماره 2، دی 2024، صفحه 3-5    اصل مقاله (260.23 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22055/rals.2024.19543
نویسندگان
Jesús García Laborda1؛ Jorge Arús Hita* 2؛ Amir Mashhadi3
1Modern Philology Department, College of Education, Universidad de Alcalá, Guadalajara, Spain
2English Studies Department, Philology College, Universidad Complutense de Madrid, Madrid, Spain
3Department of English Language and Literature, Shahid Chamran University of Ahvaz, Ahvaz, Iran
چکیده
The rapid advancement of technology, particularly artificial intelligence (AI), has had a profound impact on language assessment. Innovations such as G-Rubric, chatbots, and tools like AntConc are transforming how language proficiency is evaluated, offering new opportunities for automated feedback and enhancing Language Assessment Literacy (LAL). This special issue (SI) explores the integration of AI-aided assessment tools in various official contexts, including university entrance exams (EVAU) and Spain's Escuela Oficial de Idiomas (EOI) system. By examining these developments, we aim to provide insights into the future of language assessment in digital learning environments, focusing on how AI can facilitate more effective, equitable, and personalized language evaluation.
مراجع
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(29), 1-17. https://doi.org/10.1186/s40594-023-00418-7

Díez-Arcón, P., & Martín-Monje, E. (2021). G-rubric: The use of open technologies to provide personalised feedback in languages for specific purposes. In EDULEARN21 Proceedings (pp. 2635-2643). IATED.

Hollander, J., Sabatini, J., Graesser, A., Greenberg, D., O'Reilly, T., & Frijters, J. (2023). Importance of learner characteristics in intelligent tutoring for adult literacy. Discourse Processes: A Multidisciplinary Journal, 60(4-5), 397-409. https://doi.org/10.1080/0163853X.2023.2203543

Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning--are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237-257. https://doi.org/10.1111/jcal.12610

Kilimci, A. (2017). Integrating cognitive linguistics insights into data-driven learning: Teaching vertical prepositions. Journal of Language and Linguistic Studies, 13(2), 681-719. 

Ryan, T. (2020). Effective feedback in digital learning environments. Melbourne CSHE discussion paper. Melbourne Centre for the Study of Higher Education. https://www.proquest.com/reports/effective-feedback-digital-learning-environments/docview/2859075 907/se-2

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